Title :
Eliminating voltage violations in power systems using secondary voltage control and decentralized neural network
Author :
Mehrjerdi, H. ; Lefebvre, Serge ; Asber, Dalal ; Saad, Maarouf
Author_Institution :
Electr. Network Dept., Hydro-Quebec´s Res. Inst., Varennes, QC, Canada
Abstract :
An electrical power system is a large-scale system for which voltage control is of a significant concern for the dispatchers. For the purpose of voltage control, such a system can be partitioned into smaller size control regions. This means adapting the traditional power system to a more reliable and smart system able to cope with random and sudden load variations and disturbances. This paper investigates a decentralized neural network secondary voltage control. A number of representative buses are labeled as pilot buses displaying the critical point for voltage control in each region. The control uses decentralized neural network controllers which are attached to these pilot buses to eliminate steady-state voltage violations. The methodology is applied to the IEEE 118-bus network. The results show the performance and ability of partitioning and neural network secondary voltage control to regulate the voltage and to avoid propagation of disturbances between regions.
Keywords :
decentralised control; neurocontrollers; power system control; power system faults; random processes; voltage control; IEEE 118-bus network; decentralized neural network controller; electrical power system disturbance; pilot bus; random load variation; smart system; sudden load variation; voltage control; voltage regulation; voltage violation elimination; Artificial neural networks; Clustering algorithms; Load modeling; Partitioning algorithms; Reactive power; Training; Voltage control; Artificial Neural Network; Pilot Buses; Power Network; Secondary Voltage Control;
Conference_Titel :
Power and Energy Society General Meeting (PES), 2013 IEEE
Conference_Location :
Vancouver, BC
DOI :
10.1109/PESMG.2013.6672526